Frequency and Time-Frequency Analysis of Cutting Force and Vibration Signals for Tool Condition Monitoring

Jáuregui-Correa, Juan Carlos; Reséndiz, Juvenal Rodríguez; Thenozhi, Suresh; Szalay, Tibor; Jacsó, Ádám; Takács, Márton

doi:10.1109/access.2018.2797003

Cited by 104 publications

(41 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Figure 8 shows the architecture of the ANN being used in this research. According to TRENN [Trenn 2008], the number of hidden layers was set to 2 and the number of nodes in each hidden layer to 6. The output of the ANN is the width of cut ae.…”

Section: Description Of Methodsmentioning

confidence: 99%

“…However, this method is only validated by turning experiments, where the engagement conditions are stable throughout the process. [Salgado 2013] Other monitoring systems also rely on knowledge about the cutting path or the engagement conditions [Emec 2016;Jáuregi 2018]. There is currently no system available to detect the engagement conditions online, to support those systems.…”

Section: State Of the Artmentioning

confidence: 99%

See 1 more Smart Citation

Estimation of Engagement Conditions Using an Ann Pattern Recognition System on the Base of a Sensory Tool Holder

Bergs¹,

Schraknepper²,

Goetz³

2019

MM SJ

View full text Add to dashboard Cite

Knowledge of the tool wear state in machining has become an important issue in research and industrial application. Current systems use the spindle power or cutting force as measured variable and refer it to a taught set point. However, this method lacks the ability to adapt to new work piece geometries. This new approach focusses on the tool instead of the workpiece, and uses a sensory tool holder with integrated strain gauges. Process monitoring that is based on the increasing effect of tool wear on the cutting force requires online information of the current engagement conditions to normalize the force information. The research shown in this paper hence presents a method to estimate the width of cut in end milling. The signal of the bending torque of the tool holder in the XY-plane shows a characteristic shape for each respective engagement condition. An analytically describable relationship has been found between these shapes for different engagement conditions. On the base of this relationship, an ANN was taught to estimate the width of cut without prior knowledge of the cutting path. The results show an accurate estimation for a wide range of cutting parameters.

show abstract

Section: Description Of Methodsmentioning

confidence: 99%

Section: State Of the Artmentioning

confidence: 99%

Estimation of Engagement Conditions Using an Ann Pattern Recognition System on the Base of a Sensory Tool Holder

Bergs¹,

Schraknepper²,

Goetz³

2019

MM SJ

View full text Add to dashboard Cite

show abstract

“…The need for measuring the cutting forces caused the intervention of dynamometer as sensor measuring three directional forces acting along the x-axis, y-axis, and z-axis. The data is acquired in the form of Fast Fourier Transforms with time-frequency domain analysis from the sensor's locations of the cutting region along with position tracking [43]. One of the experimental forces is predicted from the servo drives authenticated on 5-axis machining centre of Heidenhein CNC machine.…”

Section: Dynamometer-cutting Forces Influence In Machining MMC Tool Wmentioning

confidence: 99%

A review on multi sensor data fusion technique in CNC machining of tailor-made nanocomposites

et al. 2020

View full text Add to dashboard Cite

In this study, a multiple sensor data fusion system is anticipated as essential for monitoring of cutting operations, by identifying suitable sensor locations to obtain feedback signals periodically. The sensor signal derives the failure during machining owing to complex cutting tool geometry even in machining of composites. Nano metal matrix composites (NMMC) being extremely upright in mechanical characteristics, consequently machining of these hybrid nano metal matrix composites reinforced with difficult-to-cut nano particles leads to reduced tool life thereby causing rapid flank wear. Therefore, it is a challenge to identify the wear features caused during machining of tailor made NMMC's, reducing wastage and preventing machine malfunction. This paper presents a comprehensive review on the machining strategies in extreme output conditions which rely on input parameters of speed, feed and depth of cut influencing tool life during CNC machining. This can be achieved only with multiple sensor data fusion technique during CNC machining.

show abstract

“…Obtained results indicated high effectiveness of the proposed indirect measurement method applicable also in other processes as shown in [28] for spindle vibration-based tool wear monitoring in micromilling. Jáuregui et al [29] used vibration and cutting force signals for estimating the tool condition in the highspeed micromilling process. They pointed out that the combination of two signals provided more reliable estimations with the improved sensing bandwidth.…”

Section: Review Of Related Research Workmentioning

confidence: 99%

“…6. It explains also the effectiveness of TCMSs based on cutting force signals as presented in [24,29,37,40]. Considering above, the further analysis was performed in the direction Z 3 perpendicular to the axis spindle, and parallel to the Y' axis.…”

Section: Vibration Signalsmentioning

confidence: 99%

A pilot study to assess manufacturing processes using selected point measures of vibroacoustic signals generated on a multitasking machine

Deja

Licow

2020

Int J Adv Manuf Technol

View full text Add to dashboard Cite

The article presents the method for the evaluation of selected manufacturing processes using the analysis of vibration and sound signals. This method is based on the use of sensors installed outside the machining zone, allowing to be used quickly and reliably in real production conditions. The article contains a developed measurement methodology based on the specific location of microphones and vibration transducers mounted on the tested object, in this case on a four-axis CNC ST20Y Haas lathe. A mobile phone was integrated into the measuring system and used to control the measurement process. The results from the analysis of vibration and sound signals recorded during different machining operations are presented. They refer to selected working conditions of a machine tool depending on switching the coolant supply on or off and different machine loads caused by various technological processing as well as the various speed of the positioning movements. The analysis was carried out using selected point measures describing the vibroacoustic signals. The synthesis conducted on the basis of results from the experiments indicates the validity of using vibration and acoustic signals, recorded outside the machining area, to evaluate material removal processes that are diverse in terms of kinematics and processing conditions. It indicates the possibility of using proposed point measures of vibroacoustic signals in the diagnostic aspects of the machine tools to achieve high dimension and shape accuracy and to evaluate the condition of the technological devices in terms of their optimal efficiency. Presented methodology can be used as a supporting tool in the CAD/CAM software for a better selection of appropriate cutting parameters and for a wireless control of manufacturing systems consisting of several machine tools.

show abstract

Frequency and Time-Frequency Analysis of Cutting Force and Vibration Signals for Tool Condition Monitoring

Cited by 104 publications

References 28 publications

Estimation of Engagement Conditions Using an Ann Pattern Recognition System on the Base of a Sensory Tool Holder

Estimation of Engagement Conditions Using an Ann Pattern Recognition System on the Base of a Sensory Tool Holder

A review on multi sensor data fusion technique in CNC machining of tailor-made nanocomposites

A pilot study to assess manufacturing processes using selected point measures of vibroacoustic signals generated on a multitasking machine

Contact Info

Product

Resources

About